Manganese spread in Ursa Minor as a proof of sub-classes of type Ia supernovae

Context. Recently, new sub-classes of Type Ia supernovae (SNe Ia) were discovered, including SNe Iax. The suggested progenitors of SNe Iax are relatively massive, possibly hybrid C+O+Ne white dwarfs, which can cause white dwarf winds at low metallicities. There is another class that can potentially occur at low or zero metallicities; sub-Chandrasekhar mass explosions in single and/or double degenerate systems of standard C+O white dwarfs. These explosions have different nucleosynthesis yields compared to the normal, Chandrasekhar mass explosions. Aims. We test these SN Ia channels using their characteristic chemical signatures. Methods. The two sub-classes of SNe Ia are expected to be rarer than normal SNe Ia and do not affect the chemical evolution in the solar neighbourhood; however, because of the shorter delay time and/or weaker metallicity dependence, they could influence the evolution of metalpoor systems. Therefore, we have included both in our stochastic chemical evolution model for the dwarf spheroidal galaxy Ursa Minor. Results. The model predicts a butterfly-shape spread in [Mn/Fe] in the interstellar medium at low metallicity and - at the same time - a decrease of [alpha/Fe] ratios at lower [Fe/H] than in the solar neighbourhood, both of which are consistent with the observed abundances in stars of Ursa Minor. Conclusions. The surprising agreement between our models and available observations provides a strong indication of the origins of these new sub-classes of SNe Ia. This outcome requires confirmation by future abundance measurements of manganese in stars of other satellite galaxies of ourMilkyWay. It will be vital for this project to measure not the most extreme metal-poor tail, as more commonly happens, but the opposite; the metal-rich end of dwarf spheroidals.Comment: 8 pages, 6 figures, accepted for publication in A&

The R.I. Pimenov unified gravitation and electromagnetism field theory as semi-Riemannian geometry

More then forty years ago R.I. Pimenov introduced a new geometry -- semi-Riemannian one -- as a set of geometrical objects consistent with a fibering $pr: M_n \to M_m.$ He suggested the heuristic principle according to which the physically different quantities (meter, second, coulomb etc.) are geometrically modelled as space coordinates that are not superposed by automorphisms. As there is only one type of coordinates in Riemannian geometry and only three types of coordinates in pseudo-Riemannian one, a multiple fibered semi-Riemannian geometry is the most appropriate one for the treatment of more then three different physical quantities as unified geometrical field theory. Semi-Euclidean geometry $^{3}R_5^4$ with 1-dimensional fiber $x^5$ and 4-dimensional Minkowski space-time as a base is naturally interpreted as classical electrodynamics. Semi-Riemannian geometry $^{3}V_5^4$ with the general relativity pseudo-Riemannian space-time $^{3}V^4,$ and 1-dimensional fiber $x^5,$ responsible for the electromagnetism, provides the unified field theory of gravitation and electromagnetism. Unlike Kaluza-Klein theories, where the 5-th coordinate appears in nondegenerate Riemannian or pseudo-Riemannian geometry, the theory based on semi-Riemannian geometry is free from defects of the former. In particular, scalar field does not arise. PACS: 04.50.Cd, 02.40.-k, 11.10.KkComment: 16 pages, 2 figures. Submited to Physics of Atomic Nucle

Degeneracy: a link between evolvability, robustness and complexity in biological systems

A full accounting of biological robustness remains elusive; both in terms of the mechanisms by which robustness is achieved and the forces that have caused robustness to grow over evolutionary time. Although its importance to topics such as ecosystem services and resilience is well recognized, the broader relationship between robustness and evolution is only starting to be fully appreciated. A renewed interest in this relationship has been prompted by evidence that mutational robustness can play a positive role in the discovery of adaptive innovations (evolvability) and evidence of an intimate relationship between robustness and complexity in biology. This paper offers a new perspective on the mechanics of evolution and the origins of complexity, robustness, and evolvability. Here we explore the hypothesis that degeneracy, a partial overlap in the functioning of multi-functional components, plays a central role in the evolution and robustness of complex forms. In support of this hypothesis, we present evidence that degeneracy is a fundamental source of robustness, it is intimately tied to multi-scaled complexity, and it establishes conditions that are necessary for system evolvability

Gauging the Shadow Sector with SO(3)

We examine the phenomenology of a low-energy extension of the Standard Model, based on the gauge group SU(3) x SU(2) x U(1) x SO(3), with SO(3) operating in the shadow sector. This model offers $\nu_{e} \to \nu_{s}$ and $\nu_{\mu} \to \nu_{\tau}$ oscillations as the solution of the solar and atmospheric neutrino problems. Moreover, it provides a neutral heavy shadow lepton X that could play the role of a cold dark matter particle.Comment: 8 page

The peculiar Type Ia supernova iPTF14atg: Chandrasekhar-mass explosion or violent merger?

iPTF14atg, a subluminous peculiar Type Ia supernova (SN Ia) similar to SN 2002es, is the first SN Ia for which a strong UV flash was observed in the early-time light curves. This has been interpreted as evidence for a single-degenerate (SD) progenitor system where such a signal is expected from interactions between the SN ejecta and the non-degenerate companion star. Here, we compare synthetic observables of multi-dimensional state-of-the-art explosion models for different progenitor scenarios to the light curves and spectra of iPTF14atg. From our models, we have difficulties explaining the spectral evolution of iPTF14atg within the SD progenitor channel. In contrast, we find that a violent merger of two carbon-oxygen white dwarfs with 0.9 and 0.76 solar masses, respectively, provides an excellent match to the spectral evolution of iPTF14atg from 10d before to several weeks after maximum light. Our merger model does not naturally explain the initial UV flash of iPTF14atg. We discuss several possibilities like interactions of the SN ejecta with the circum-stellar medium and surface radioactivity from a He ignited merger that may be able to account for the early UV emission in violent merger models.Comment: 12 pages, 7 figures, accepted for publication in MNRA

Inferring hidden Markov models from noisy time sequences: a method to alleviate degeneracy in molecular dynamics

We present a new method for inferring hidden Markov models from noisy time sequences without the necessity of assuming a model architecture, thus allowing for the detection of degenerate states. This is based on the statistical prediction techniques developed by Crutchfield et al., and generates so called causal state models, equivalent to hidden Markov models. This method is applicable to any continuous data which clusters around discrete values and exhibits multiple transitions between these values such as tethered particle motion data or Fluorescence Resonance Energy Transfer (FRET) spectra. The algorithms developed have been shown to perform well on simulated data, demonstrating the ability to recover the model used to generate the data under high noise, sparse data conditions and the ability to infer the existence of degenerate states. They have also been applied to new experimental FRET data of Holliday Junction dynamics, extracting the expected two state model and providing values for the transition rates in good agreement with previous results and with results obtained using existing maximum likelihood based methods.Comment: 19 pages, 9 figure

Surface networks

© Copyright CASA, UCL. The desire to understand and exploit the structure of continuous surfaces is common to researchers in a range of disciplines. Few examples of the varied surfaces forming an integral part of modern subjects include terrain, population density, surface atmospheric pressure, physico-chemical surfaces, computer graphics, and metrological surfaces. The focus of the work here is a group of data structures called Surface Networks, which abstract 2-dimensional surfaces by storing only the most important (also called fundamental, critical or surface-specific) points and lines in the surfaces. Surface networks are intelligent and “natural ” data structures because they store a surface as a framework of “surface ” elements unlike the DEM or TIN data structures. This report presents an overview of the previous works and the ideas being developed by the authors of this report. The research on surface networks has fou